```VILLANOVA UNIVERSITY
College of Commerce and Finance
SYLLABUS
Statistics
CMB 8015 - 001
Fall 2006
E. Mathis
Professor
Office
Office Hours
Office Phone
Fax Number
Email
Edward J. Mathis
Bartley 3048
Thursday 3:30-5:00
Other by Appointment
610-519-4387 Off Campus 610-356-5800
610-519-6054
[email protected]
Course Successful completion of a college level Calculus course.
Prerequisites
It is the student’s responsibility to be certain that the prerequisite has been
successfully completed. If at any time during the semester it is determined
that a student has not completed the prerequisites, the student can be
administratively dropped from the course without credit or tuition refund.
Required Levine, David M., Stephan, David, Krehbiel, Timothy C., and Berenson,
Text Mark L., Business Statistics: A First Course . Prentice-Hall, 2006 (4th
Edition)
Course The introduction of statistical concepts and methods useful in analyzing
Description problems in all areas of business and economics. In addition to learning the
concepts, applications will be addressed in: Probability, Discrete Probability
Distributions, Sampling Distributions, Confidence Intervals, Hypothesis
Testing and Regression Analysis.
Objectives Given successful completion of the Introduction to Statistical Analysis
course, you will be able to:
1.
2.
3.
4.
Recognize business situations that require the use of
statistical tools of analysis.
Select and execute appropriate statistical tools for specific
Use the statistical tools of analysis and statistical software
(EXCEL, SPSS) in making business decisions.
Incorporate appropriate ethical considerations in using the
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tools of statistical analysis.
Specifically, after completing this course, the student will be able to:
Use Descriptive Statistics and Probability Distributions
A.
B.
C.
D.
E.
F.
G.
Distinguish between descriptive and inferential statistics.
Effectively present data in the form of tables, charts, graphs,
etc.
Calculate and interpret measures of central tendency and
each.
Use the measures of central tendency and variation to
describe data sets and make comparisons
Understand the rules of probability and their applications;
calculate probabilities by applying the rules of addition and
multiplication.
Apply Bayes theorem in the business environment.
Identify discrete and continuous probability distributions and
use them to analyze business situations.
Apply Methods of Inferential Statistics
H.
I.
J.
Explain why a sample is the only feasible way to learn about
a population and recognize various techniques for taking a
sample.
Use statistical inference (confidence intervals) to estimate
population characteristics such as the mean, proportion,
difference of two means, and difference of two proportions.
Draw conclusions concerning population characteristics by
conducting tests of hypothesis.
Analyze using Regression and Correlation Techniques
K.
L.
Describe the relationship between a dependent variable and
one or more independent variables.
Conduct simple and multiple regression and correlation
analysis
Communicate Effectively and Address Ethical Issues
M.
N.
Generate and interpret statistical results from computer
software such as EXCEL or SPSS.
Write an executive summary and/or report to analyze either
an original business problem using statistical techniques or a
2
O.
Topical I.
Coverage
case study offered by the professor.
Recognize that statistical techniques can be used either
improperly or unethically
Descriptive Statistics and Probability Distributions (Chapters
1,2,3,4,5,6)
II.
Methods of Inferential Statistics (Chapters (7,8,9,10)
III.
Correlation and Regression Analysis (Chapters 12,13)
A detailed schedule of topical coverage is found at the end of the syllabus.
To assist with the analysis of the chapter problems, homework and class
discussions, the course will use Microsoft Excel and PH Stat II . Ethical
business situations will be discussed where applicable.
Teaching The class will meet for lectures and discussion on the theory and
Method applications of statistics. All students are expected to have attempted
relevant problems before class. Class participation will be encouraged and
expected. The class will move at a rapid pace in order to cover all the
necessary material. Please do not fall behind.
This course will be taught in two parts. In the first part of the course, the
basic tools of descriptive statistics will be reviewed and introduced. These
topics include descriptive statistics, probability theory, discrete distributions
and continuous distributions. The second part of the course will deal with
inferential statistics and applied statistical methods including estimation,
hypothesis testing, regression analysis and time series analysis. Ethical
business situations will be discussed with respect to the appropriate
statistical tool.
If you have a disability that may affect your success in this course and wish
soon as possible and not later than the end of the second week of the
semester.
Homework Homework problems will be assigned for each chapter after the class has
Assignments been taught. The assignment will be emailed to you. After they are assigned
I will email the solutions to the problems on the Tuesday after the class
from which they were assigned and before the next class. Questions about
the homework assignments will be answered at the beginning of the next
class. It is the responsibility of every student to work out the assigned
problems. Homework will not be collected but it is easier to understand the
subsequent, cumulative material if assignments are completed on a timely
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basis.
Many of the homework assignments will come from the Practice Problems
Project Students are required to do a computer project using regression and
correlation analysis. Detailed instructions for the project will be emailed in
October. The report on this project is due on December 19, 2006. There is a
penalty if the project is late.
Attendance It is important that students attend all classes and be prepared prior to the
class. Attendance is critical because some course material is developed that
is not directly covered in the text or is presented in a different way.
of the subject matter. Students who miss a class are responsible for any
assignments. Attendance records may be kept and have some relevance in
Grade A midterm examination, a computer project using regression and correlation
Determination analysis and a final examination will be among the testing tools used. The
examinations are cumulative. Class participation is taken into consideration,
especially if one has a grade that is in a borderline position.
All examinations are open book and open notes. The computer will be used
in all exams.



Midterm Exam – 30%
Final Exam
– 50%
Project
- 20%
THERE WILL BE NO EXTRA CREDIT.
Exam 
Schedule 

Midterm Exam I – Thursday, October 26,2006
Project Due Date – Tuesday, December 19, 2006
Final Exam - Thursday, December 14, 2006
Make-up All make-ups are scheduled at a common time AFTER the end of the
Exam Policy semester.
Computer To assist with the analysis of the chapter problems and class discussions,
Materials this course will use Microsoft Excel. Instructions on using Microsoft Excel
are included in special Excel sections of the text chapters. A statistics add-in
for Microsoft Excel, called PHStat2, is included on the CD-ROM that
accompanies the text. Make sure that the CD-ROM is included if you buy a
used textbook. Since this is a new edition of the textbook, it is strongly
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Integrity fabrication of submitted work, plagiarism, handing in work completed for
Policy another course without the instructor’s approval, and other forms of
dishonesty. For the first offense, a student who violates the Code of
Villanova University will receive 0 (zero) points for the assignment. The
violation will be reported by the instructor to the Dean’s Office and
recorded in the student’s file. In addition, the student will be expected to
complete an education program. For the second offense, the student will be
dismissed from the University and the reason noted on the student’s official
transcript.
Week
Class
Date
Topics
1- 2
August 24
&
31
Descriptive
Statistics
3-4
September
7 & 14
Basic
Probability
and Discrete
Probability
Distributions
Chapte
r
Content
1,2,3




..
Organization of Data
Measures of central tendency
Measures of dispersion
Shape of a distribution
4,5



Classical, relative frequency and subjective
probabilities
Sample spaces and events
Contingency tables and Venn diagrams
Simple marginal probability
Joint probability
General multiplication rule and independence
Conditional probability
Bayes Theorem
Counting methods (optional)
 Multiplication of choices
 Permutation
Combination
Probability distribution for a random variable
Discrete probability distributions
Expected value of a probability and its
Standard deviation of a probability distribution
Binomial distribution
Poisson distribution (optional)
6

Introduction to Normal Distribution
7


Sampling and Sampling Distributions
Central Limit Theorem (for sample mean)














5-6
September
21
September
28
Normal
Distribution
Sampling
and
5
7
October 5
Sampling
Distributions
Estimation
8

Distribution for Sample Proportion

Point estimate and interval estimate for a
population parameter
Confidence interval for a population mean or
proportion
 The z-distribution
 The t-distribution
Sample size for the population mean and
population proportion
Finite population correction factor



8
October
19
Hypothesis
Testing
9
October
26
November
2&9
Midterm
exam
Hypothesis
Testing
12 – 14
November
16 & 30
December
7
Simple and
Multiple
Regression
Analysis
15
December
14
Final Exam
10 – 11
9


Type I and Type II error
Test of single means and proportions and
P values
9,10


12,13





Two sample tests of means and proportions
Determination of sample size to control Type I
and Type II error
Simple regression analysis
Correlation analysis
Tests in simple regression
Multiple regression analysis
Problems in regression analysis
6
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